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Evaluation of Using Remote Sensing Evapotranspiration Data in SWAT

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Abstract

This study applied a time series evapotranspiration (ET) data derived from the remote sensing to evaluate Soil and Water Assessment Tool (SWAT) model calibration, which is a unique method. The SWAT hydrologic model utilized monthly stream flow data from two US Geological Survey (USGS) stations within the Big Sunflower River Watershed (BSRW) in Northwestern, Mississippi. Surface energy balance algorithm for land (SEBAL), which utilized MODerate Resolution Imaging Spectro-radiometer (MODIS) to generate monthly ET time series data images were evaluated with the SWAT model. The SWAT hydrological model was calibrated and validated using monthly stream flow data with the default, flow only, ET only, and flow-ET modeling scenarios. The flow only and ET only modeling scenarios showed equally good model performances with the coefficient of determination (R2) and Nash Sutcliffe Efficiency (NSE) from 0.71 to 0.86 followed by flow-ET only scenario with the R2 and NSE from 0.66 to 0.83, and default scenario with R2 and NSE from 0.39 to 0.78 during model calibration and validation at Merigold and Sunflower gage stations within the watershed. The SWAT model over-predicted ET when compared with the Modis-based ET. The ET-based ET had the closest ET prediction (~8% over-prediction) as followed by flow-ET-based ET (~16%), default-based ET (~27%) and flow-based ET (~47%). The ET-based modeling scenario demonstrated consistently good model performance on streamflow and ET simulation in this study. The results of this study demonstrated use of Modis-based remote sensing data to evaluate the SWAT model streamflow and ET calibration and validation, which can be applied in watersheds with the lack of meteorological data.

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Acknowledgements

We would like to acknowledge the partial financial support of AFRI competitive grant award # 2013-67020-21407 and 2017-67020-26375, from the USDA/NIFA; and Special Research Initiatives of the Mississippi Agricultural and Forestry Experiment Station at Mississippi State University. We would like to acknowledge the support of Yazoo Mississippi Delta Joint Water Management District; USGS; and all our collaborators.

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Authors and Affiliations

  1. Department of Agricultural and Biological Engineering, Mississippi State University, Mississippi State, MS, USA

    Prem B. Parajuli

  2. New South Wales Department of Primary Industries, Orange, NSW, Australia

    Priyantha Jayakody

  3. USDA Forest Service, Mississippi State, MS, USA

    Ying Ouyang

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  1. Prem B. Parajuli
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  2. Priyantha Jayakody
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  3. Ying Ouyang
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Correspondence to Prem B. Parajuli.

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Parajuli, P.B., Jayakody, P. & Ouyang, Y. Evaluation of Using Remote Sensing Evapotranspiration Data in SWAT. Water Resour Manage 32, 985–996 (2018). https://doi.org/10.1007/s11269-017-1850-z

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